Objective:To evaluate the accuracy of a self-developed extraoral scanning system based on photogrammetry technology, and to provide evidence for advancing the development and clinical application evaluation of domestically produced scanning devices.Methods:This research group developed a photogrammetry-based implant extraoral scanning system with customized scan bodies. Two distinct edentulous implant resin models were designed and three-dimensional (3D)-printed by Center of Digital Dentistry, Peking University School and Hospital of Stomatology, containing 6 (Model 1) and 8 (Model 2) abutment analogs respectively. Reference data acquisition was performed using a high-precision denture 3D scanner with scan caps mounted on the analogs. Specialized scan bodies were then mounted on the analogs for 3D positional data acquisition using both the self-developed system (experimental group) and the clinically established system (control group). Each system conducted 10 repeated scans per model. Trueness was assessed through root mean square error (RMSE), linear deviation (LD), and angular deviation (AD) relative to reference data, while precision was determined through intra-group RMSE analysis. Systematic comparisons included inter-group performance on identical models and intra-group variability across different models.Results:For Model 1, the experimental group showed statistically significant advantages over controls in intra-group RMSE [(3.10±0.71) μm vs (4.61±1.51) μm, P<0.001], reference-data RMSE [(21.48±0.60) μm vs (32.50±0.63) μm, P<0.001], linear deviation [23.64 (32.35) μm vs 44.86 (55.73) μm, P<0.001], and angular deviation [0.29° (0.29°) vs 0.23° (0.33°), P<0.001]. In Model 2, significant improvements were observed in intra-group RMSE [(4.47±1.58) μm vs (6.21±2.07) μm, P<0.001], reference-data RMSE [(38.84±0.86) μm vs (43.69±1.34) μm, P<0.001], and linear deviation [37.95 (50.68) μm vs 49.71 (58.89) μm, P<0.001]. Both groups exhibited model-dependent variability, with RMSE of precision and trueness of both groups, linear deviation of experimental group, angular deviation of control group showing statistically significant increases (all P<0.001) corresponding to abutment analog quantity. Conclusions:The self-developed scanning system demonstrates superior accuracy in 3D positional acquisition of abutment analogs compared to the contral group system, with implant number identified as a critical determinant of extraoral scanning accuracy.

Objective:To evaluate the accuracy of the oral healthcare information provided by different large language models (LLM) to explore their feasibility and limitations in the application of oral auxiliary, treatment and health consultation.Methods:This study designed eight items comprising 47 questions in total related to the diagnosis and treatment of oral diseases [to assess the performance of LLM as an artificial intelligence (AI) medical assistant], and five items comprising 35 questions in total about oral health consultations (to assess the performance of LLM as a simulated doctor). These questions were answered individually by the five LLM models (Erine Bot, HuatuoGPT, Tongyi Qianwen, iFlytek Spark, ChatGPT). Two attending physicians with more than 5 years of experience independently rated the responses using the 3C criteria (correct, clear, concise), and the consistency between the raters was assessed using the Spearman rank correlation coefficient, and the Kruskal-Wallis test and Dunn post hoc test were used to assess the statistical differences between the models. Additionally, this study used 600 questions from the 2023 dental licensing examination to evaluate the time taken to answer, scores, and accuracy of each model.Results:As an AI medical assistant, LLM can assist doctors in diagnosis and treatment decision-making, with an inter-evaluator Spearman coefficient of 0.505 ( P<0.01). As a simulated doctor, LLM can carry out patient popularization, with an inter-evaluator Spearman coefficient of 0.533 ( P<0.01). The 3C scores of each model as an AI medical assistant and a simulated doctor were respectively: 2.00 (1.00, 3.00) and 2.00 (2.00, 3.00) points of Erine Bot, 1.00 (1.00, 2.00) and 2.00 (1.00, 2.00) points of HuatuoGPT, 2.00 (1.00, 2.00) and 2.00 (1.00, 3.00) points of Tongyi Qianwen, 2.00 (1.00, 2.00) and 2.00 (1.75, 2.25) points of iFlytek Spark, 3.00 (2.00, 3.00) and 3.00 (2.00, 3.00) points of ChatGPT (full score of 4 points). The Kruskal-Wallis test results showed that, as an AI medical assistant or a simulated doctor, there were statistically differences in the 3C scores among the five large language models (all P<0.001). The average score of the 5 LLMs on the dental licensing examination was 370.2, with an accuracy rate of 61.7% (370.2/600) and a time consumption of 94.6 min. Specifically, Erine Bot took 115 min, scored 363 points with an accuracy rate of 60.5% (363/600), HuatuoGPT took 224 min and scored 305 points with an accuracy rate of 50.8% (305/600), Tongyi Qianwen took 43 min, scored 438 points with an accuracy rate of 73.0% (438/600), iFlytek Spark took 32 min, scored 364 points with an accuracy rate of 60.7% (364/600), and ChatGPT took 59 min, scored 381 points with an accuracy rate of 63.5% (381/600). Conclusions:Based on the evaluation of LLM′s dual roles as an AI medical assistant and a simulated doctor, ChatGPT performes the best, with basically correct, clear and concise answers, followed by Erine Bot, Tongyi Qianwen and iFlytek Spark, with HuatuoGPT lagging behind significantly. In the dental licensing examination, all the 4 LLM, except for HuatuoGPT, reach the passing level, and the time consumpution for answering is significantly reduced compared to the 8 h required for the exam regulations in all of the five models. LLM has the feasibility of application in oral auxiliary, treatment and health consultation, and it can help both doctors and patients obtain medical information quickly. Howere, their outputs carry a risk of errors (since the 3C scoring results do not reach the full marks), so prudent judgment should be exercised when using them.

Professor Zheng Linfan has played an important role in pioneering and leading the development of dentistry in China. In the early 1940s, he spearheaded groundbreaking investigations on the oral health status of Chinese students, and guided fundamental researches by clinical issues which led to the establishment of China′s first oral histopathology laboratory and the Institute of Stomatology. His remarkable scholarly achievements earned him the National Medical and Health Science Conference Award in 1978. He attached great importance to "investigation and clinical practice", "basic research-driven", "interdisciplinary" and "international cooperation and exchange" in the early stage of the development of oral science in China, and therefore formed a four-in-one innovative idea, making important contributions to the innovative research and clinical development of Chinese stomatology. This article bases on professor Zheng Linfan′s work and research experience. Through the excavation of archival documents, correspondence, memoirs, historical records, and oral history materials, this article reconstructs his contributions to stomatology in China, and summarizes his academic ideas, practical paths, and ideological values in promoting the construction of the stomatological development system, providing references for enriching the historical narrative of stomatology in China, and assisting contemporary advancements and technological innovation.

Vertical root fracture (VRF) often occurs in endodontically treated teeth. Root canal therapy (RCT) requires removal of part of the dentin, which affects the microhardness and elastic modulus of dentine, induces dentin microcracks, and increases the risk of VRF. The early diagnosis of VRF is challenging and the prognosis is poor, due to the absence of specific clinical manifestations. This narrative review analyzes the incidence and related factors of VRF after RCT from the perspective of etiology, discusses the effect and mechanism of each step during RCT on the occurrence of VRF, and briefly summarizes the diagnosis, prevention and treatment strategies of VRF, so as to reduce the occurrence of VRF and improve the prognosis of endodontically treated teeth.

This study provides a comprehensive review of the development and achievements in the field of oral genetic disorders research in China. Since the 1950s, Chinese scholars have progressed from epidemiological surveys to the elucidation of molecular mechanisms and functional genomics, marking a transition from macro-level observations to micro-level analyses. The research focuses on three major categories: cleft lip and palate, dental developmental anomalies, and rare hereditary oral diseases. Several critical pathogenic genes have been identified, and their molecular mechanisms and phenotypic characteristics elucidated. This paper summarizes representative findings, analyzes current challenges, and outlines future research directions, aiming to provide theoretical support for advancing both basic research and clinical translation in the field of oral genetics in China.

Pemphigus vulgaris (PV) is a group of autoimmune bullous diseases characterized by life-threatening intradermal blisters. Hashimoto thyroiditis (HT) is a kind of autoimmune disease with abnormal increase of thyroid peroxidase autoantibody (TPOAb), which is the thyroid specific antibody, leading to hypothyroidism. In recent years, the probability of HT in patients with PV is increasing, and the co-disease may be related to the effect of TPOAb autoantibody on oral keratinocytes. This article reviews the epidemiological relationship between PV and HT and the mechanism of TPOAb in their co-disease, in order to provide ideas for the diagnosis and treatment of both.

Periodontitis constitutes the primary cause of tooth loss among adults in China. The disease is characterized by the high morbidity, which significantly impairs both oral and systemic health. As the key insights of initial periodontal therapy, subgingival scaling and root planing (SRP) have been considered as simple, effective, and cost-efficient treatment approaches for managing periodontal inflammation. Substantial published evidences indicated that the majority of patients diagnosed with periodontitis could achieve lifelong retention of their natural teeth through standardized initial periodontal therapy, rigorous plaque control, and long-term supportive periodontal treatment. However, the proficiency in periodontal diagnosis and treatment among general dental practitioners in China is heterogeneous, with a notable scarcity of periodontists and a suboptimal level of SRP standardization. Drawing upon over four decades of clinical expertise from Peking University School and Hospital of Stomatology as well as comprehensive literature reviews, this paper meticulously outlines the standardized procedures for SRP, aiming at guiding clinicians to perform standardized SRP step by step, and thereby enhancing clinical efficacy of periodontal treatment, promoting periodontal health, and ultimately improving patients′ quality of life.

Insufficient keratinized mucosa is a common clinical problem. Although there is no consistent data on the long-term success of implant restorations relative to the presence or absence of peri-implant keratinized mucosa, it is widely accepted that the presence of keratinized mucosa width<2 mm is associated with increased biofilm accumulation, soft-tissue inflammation, and mucosal recession. Free gingival graft (FGG) is the standard surgical intervention for augmenting the width of keratinized gingiva. However, the clinical application of FGG is technique-sensitive. Therefore, this article describes the significance and efficacy, surgical timing, conventional procedures and techniques, common complications, as well as some modified approaches of the FGG, aiming to provide guidelines for its clinical application.

To better reflect the current status and key research trends in oral medicine research of China and to enhance the overall research abilities in this field, this special issue on oral medicine research integrates the work of several young academic leaders from oral medicine research centers nationwide. Their work focuses on key areas such as artificial intelligence-assisted diagnosis, the pathogenic mechanisms of intracellular bacteria, the relations between oral mucosal diseases and systemic diseases, as well as the study and reporting of rare and unique cases, aligning with the forefront of biomedical research. Although it does not encompass all the high-level researches conducted in China, it presents a rich and diverse array of academic achievements. Those achievements of researches reflect that it is important to further advance interdisciplinary and cross-disciplinary research collaborations, particularly by strengthening cooperation with engineering and technological disciplines in the future. We also need to set sights on driving researches in novel pathogenesis mechanisms of oral mucosal diseases, exploring innovative diagnostic technologies, enhancing diagnostic accuracy and treatment efficacy, and developing new effective intervention strategies. Additionally, greater emphases will be placed on ensuring the accuracy, comprehensiveness, readability, and scientific rigor of case studies and reports to promote sustained progress in this field.

Objective:Comprehensive characterization of B-cell phenotypes and spatial distribution in oral lichen planus (OLP) and related oral lichenoid lesions (OLL)(OLP/OLL), with an emphasis on transcriptomic profiling and functional analysis, to uncover the epigenetic mechanisms underlying B cell-mediated immune regulation within the oral mucosal microenvironment.Methods:Single-cell RNA sequencing raw data were sourced from the GSE211630 database, encompassing samples from 2 cases of erosive OLP (EOLP), 3 cases of non-erosive OLP (NEOLP) and 1 healthy control (NORMAL). Following stringent quality control, the data underwent normalization, selection of highly variable genes and batch effect correction. Subsequent analyses included dimensionality reduction and unsupervised clustering to identify distinct cell populations. This study collected pathological specimens from 3 OLP/OLL patients and 3 healthy controls who were treated at the Department of Oral Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine from January 2021 to December 2023. Using 10X Genomics Visium HD spatial transcriptomics technology, tissue sections were processed through dewaxing, staining and histological imaging, enabling the reconstruction of nucleic acid structures and the capture of gene expression profiles. Data analysis included quality assessment, gene quantification, normalization, dimensionality reduction and clustering. Furthermore, cell type deconvolution was performed using the robust cell type decomposition algorithm, integrating single-cell transcriptomic data to accurately predict and spatially resolve cell type distributions within the tissue microenvironment.Results:After integrating single-cell data from EOLP, NEOLP and NORMAL, cells were classified into seven major categories: B/plasma cells, endothelial cells, epithelial cells, fibroblasts, myeloid cells, smooth muscle cells and T/natural killer cells. The proportion of B/plasma cells varied significantly among the three groups, accounting for 10.7% (1 693/15 815), 3.8% (833/21 653) and 0.4% (47/11 556) of the total cells respectively. Further clustering analysis of B/plasma cells identified four distinct subpopulations: naive B cells, activated B cells, memory B cells and plasma cells. In the EOLP group, these subpopulations constituted 25.9% (348/1 344), 45.9% (617/1 344), 3.3% (45/1 344) and 24.9% (334/1 344) of the B/plasma cells respectively. In the NEOLP group, they represented 31.6% (195/617), 59.6% (368/617), 0.2% (1/617) and 8.6% (53/617). Howerer, only plasma cells were detected in the NORMAL group. Spatial analysis revealed that B cells were actively involved in the formation of tertiary lymphoid structures (TLS) at various stages in OLP/OLL samples, with a prominent structural organization observed in secondary follicle-like TLS. Within these structures, the expressions of T cells marker gene CD3E and B cells marker gene MS4A1 were significantly elevated. Additionally, in secondary follicle-like TLS, the gene encoding follicular dendritic cell secreted protein, germinal center marker gene B cell lymphoma 6 and the gene for activation induced cytidine deaminase also showed strong expression. In OLP/OLL samples, plasma cell marker gene CD38, immunoglobulin (IGH) G3, IGHG1, IGHM, IGHD, IGHE, imunoglobulin Kappa constant, immunoglobulin alpha 1, immunoglobulin Lambda constant 1 and complement gene C3 all exhibited high levels of expression.Conclusions:Compared to normal mucosa, extensive B-cell infiltration is observed in both OLP and OLL, accompanied by significant differences in B-cell phenotypes and proportions. B cells appear to play a central role in local immune responses, primarily through the formation of TLS. However, the precise functional mechanisms underlying their involvement require further investigation.